Package: mlsurvlrnrs 0.0.4
mlsurvlrnrs: R6-Based ML Survival Learners for 'mlexperiments'
Enhances 'mlexperiments' <https://CRAN.R-project.org/package=mlexperiments> with additional machine learning ('ML') learners for survival analysis. The package provides R6-based survival learners for the following algorithms: 'glmnet' <https://CRAN.R-project.org/package=glmnet>, 'ranger' <https://CRAN.R-project.org/package=ranger>, 'xgboost' <https://CRAN.R-project.org/package=xgboost>, and 'rpart' <https://CRAN.R-project.org/package=rpart>. These can be used directly with the 'mlexperiments' R package.
Authors:
mlsurvlrnrs_0.0.4.tar.gz
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mlsurvlrnrs.pdf |mlsurvlrnrs.html✨
mlsurvlrnrs/json (API)
# Install 'mlsurvlrnrs' in R: |
install.packages('mlsurvlrnrs', repos = c('https://kapsner.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/kapsner/mlsurvlrnrs/issues
algorithmscox-regressionexperimentsglmnetlearnersmachine-learningrandom-survival-forestssurvivalsurvival-support-vector-machinexgboost
Last updated 5 months agofrom:34c6cfcb0e. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 04 2024 |
R-4.5-win | OK | Nov 04 2024 |
R-4.5-linux | OK | Nov 04 2024 |
R-4.4-win | OK | Nov 04 2024 |
R-4.4-mac | OK | Nov 04 2024 |
R-4.3-win | OK | Nov 04 2024 |
R-4.3-mac | OK | Nov 04 2024 |
Exports:c_indexLearnerSurvCoxPHCoxLearnerSurvGlmnetCoxLearnerSurvRangerCoxLearnerSurvRpartCoxLearnerSurvXgboostAftLearnerSurvXgboostCox
Dependencies:backportsbase64encbslibcachemcheckmatecliclustercodetoolscolorspacecrayondata.tabledigestdoParallelevaluatefansifarverfastmapfontawesomeforeachforeignFormulafsggplot2gluegridExtragtablehighrHmischmshtmlTablehtmltoolshtmlwidgetsisobanditeratorsjquerylibjsonlitekdryknitrlabelinglatticelifecyclemagrittrMASSMatrixmemoisemgcvmimemlexperimentsmllrnrsmunsellnlmennetpillarpkgconfigprettyunitsprogressR6rappdirsRColorBrewerrlangrmarkdownrpartrstudioapisassscalessplitToolsstringistringrtibbletinytexutf8vctrsviridisviridisLitewithrxfunyaml
glmnet: Survival Analysis
Rendered frommlsurvlrnrs_glmnet_survival.qmd
usingquarto::html
on Nov 04 2024.Last update: 2024-05-29
Started: 2024-05-29
ranger: Survival Analysis
Rendered frommlsurvlrnrs_ranger_survival.qmd
usingquarto::html
on Nov 04 2024.Last update: 2024-05-29
Started: 2024-05-29
rpart: Survival Analysis
Rendered frommlsurvlrnrs_rpart_survival.qmd
usingquarto::html
on Nov 04 2024.Last update: 2024-05-29
Started: 2024-05-29
xgboost: Survival Analysis, AFT Analysis
Rendered frommlsurvlrnrs_xgboost_survival_aft.qmd
usingquarto::html
on Nov 04 2024.Last update: 2024-05-29
Started: 2024-05-29
xgboost: Survival Analysis, Cox Regression
Rendered frommlsurvlrnrs_xgboost_survival_cox.qmd
usingquarto::html
on Nov 04 2024.Last update: 2024-05-29
Started: 2024-05-29
Readme and manuals
Help Manual
Help page | Topics |
---|---|
c_index | c_index |
R6 Class to construct a Cox proportional hazards survival learner | LearnerSurvCoxPHCox |
R6 Class to construct a Glmnet survival learner for Cox regression | LearnerSurvGlmnetCox |
R6 Class to construct a Ranger survival learner for Cox regression | LearnerSurvRangerCox |
LearnerSurvRpartCox R6 class | LearnerSurvRpartCox |
R6 Class to construct a Xgboost survival learner for accelerated failure time models | LearnerSurvXgboostAft |
R6 Class to construct a Xgboost survival learner for Cox regression | LearnerSurvXgboostCox |